In this project we develop new methods for the fast and reliable analysis of extracellular data. We currently focus on the detection and classification of action potentials in voltage traces which are recorded simultaneously, for example, using multi-electrode and multi-tetrode arrays. Our approach makes use of linear filters to find a new representation of the data and to optimally enhance the signal-to-noise ratio, makes use of source separation techniques to decorrelate filter outputs. The developed methods are able to separate overlapping spikes and can adapt to non-stationary data. Therefore, they are well suited for acute recordings, where they allow for on-line spike-sorting and -analysis. Together with Dr. M. Munk (MPI for Biological Cybernetics) our methods are currently being evaluated on data recorded from awake behaving monkeys during visual working memory tasks. Current collaboration partners include but are not limited to the University of Freiburg, the University of Oslo, the Max Planck Institute for Biological Cybernetics (Tübingen), Thomas RECORDING GmbH (Gießen) and the German Neuroscience Node (GNode).
Acknowledgements: Research is funded by BMBF (via the Bernstein Center and a Bernstein Collaboration) and the Technische Universität Berlin.